id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-331897-4wnoa4l7	Cai, Yi	Temporal event searches based on event maps and relationships()	2019-09-25		.txt	text/plain	10502	595	61	Experiments conducted on a real data set show that our method outperforms the baseline method Event Evolution Graph (EEG), and it can help discover certain new relationships missed by previous methods and even by human annotators. Although some work has been done to find and link incidents in news stories [4, 5] or discover event evolution graphs [6, 7] , this scholarship has only focused on time sequences and content similarity between two component events to identify the dependence relationships. To the best of our knowledge, this is the first piece of work that (1) formalizes and handles the event search problem by analyzing all temporal, content dependence and event reference relationships between events to construct an overall picture of the event's evolution; and (2) measures the importance of events based on the interrelationships of events.	./cache/cord-331897-4wnoa4l7.txt	./txt/cord-331897-4wnoa4l7.txt